Many applications require that objects be "tagged" so that the object can be identified or so that information about the object can be provided to a data acquisition system. One type of tagging is the use of bar codes on objects. Bar coding of objects, e.g. for identifying objects in a retail check out line, is well known. However, the use of bar codes requires a code reader at close proximity, and very often, the presence or assistance of a human being. Accordingly there is a growing need for devices that can operate over larger distances, and where the identification process can be entirely automated.
The prior art discloses objects being tagged with unique frequencies or unique frequency patterns for purposes of identification. In this type of tagging, called frequency tagging, the object would have a type of transmitter that would send a frequency signal to a remote receiver. The receiver uses the signal and/or the frequency or frequency pattern of the signal to identify the object and/or obtain information about the object. These applications of frequency tagging may involve, for instance, applications that require tagging of objects in stores, for purposes of sales and inventory, or applications for identifying automobiles on a toll road at a toll stop for the purpose of collecting a toll.
In digital communication systems digital packet transmissions can be preceded by unique frequency tones so that the transmission medium may be characterized by determining a set of parameters that fully represent the effect of the medium upon the transmission. These parameters are typically determined prior to the actual data transmission and are used to filter the effects of the medium from the signal. This characterization is also called channel estimation, e.g., identification of the noise in the signal. Once identified, the noise can be removed.
Other applications of frequency tagging exist in magnetic recording, where pilot tones e.g., audio, frequencies are employed to provide position reference information in order to maintain a magnetic head over a track. One common choice of frequencies for tagging objects in the prior art are radio frequencies. The tagged object is fitted with an active or passive device that responds to a query from a transceiver. In a system using active device tags, the object has a device such as a transceiver that emits a unique set of radio frequency tones. In a system using passive device tags, the object has a device that may resonate at unique frequencies when queried by specific frequency tones. Alternatively, a passive device may have a uniquely shaped antenna that couples to the antenna of the interrogating source, and thereby conveys its information in a unique frequency tone. In any event, these frequencies must be uniquely identified and used to establish the identity of the queried object.
However, the prior art sometimes has problems in resolving frequency patterns, i.e., the prior art sometimes has problems identifying all the component frequencies of a frequency pattern. These problems particularly arise when the frequency patterns are made up of a set of frequencies that are very close together. Frequency patterns are also difficult to resolve if there is noise in the signal, especially if the noise is not deterministic. A noise is not deterministic, e.g., indeterministic, if the cause and/or structure of the noise are unknown. (Knowledge about the structure of noise includes a definition of the frequencies making up the noise, the amplitudes and phases of those frequencies, and the distribution of the frequencies.)
The prior art often try to resolve transmitted frequency patterns using methods based on Fourier techniques. However, these techniques cannot resolve frequency patterns well if the frequencies in the pattern are spaced closer than 1/N, where N is the number of samples of the signal available. For example, if the number of samples of a signal is 100, the prior art can not distinguish between two frequencies spaced closer than 0.01 cycles per second. When the frequencies in the pattern are spaced this close or closer, the two frequencies appear as one to the receiver.
Many analog and digital systems in the prior art also fail to resolve frequency patterns with frequencies space closer than 1/N because of the closeness of the frequencies making up the pattern and the tuning limitations of the hardware.
To resolve a pattern of frequencies containing noise, the prior art uses a number of techniques that presuppose a certain noise background and describe methods for identifying frequencies embedded in these presupposed noise backgrounds. This process of noise estimation and the estimation of the location in frequency domain, of the unique frequency tones, together with estimation of the amplitude and phase content in the unique frequencies is usually termed channel estimation. However, channel estimation techniques fail to work well in the presence of indeterministic noise because most techniques are designed to filter an assumed noise structure and are inadequate to filter other noise structures.